Package: mogsa 1.41.0

Chen Meng

mogsa: Multiple omics data integrative clustering and gene set analysis

This package provide a method for doing gene set analysis based on multiple omics data.

Authors:Chen Meng

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mogsa.pdf |mogsa.html✨
mogsa/json (API)
NEWS

# Install 'mogsa' in R:

install.packages('mogsa', repos = c('https://bioc.r-universe.dev', 'https://cloud.r-project.org'))

Datasets:

NCI60_4array_supdata - Supp data for Microarray gene expression profiles of the NCI 60 cell lines from 4 different platforms
NCI60_4arrays - Microarray gene expression profiles of the NCI 60 cell lines from 4 different platforms

On BioConductor:mogsa-1.41.0(bioc 3.21)mogsa-1.40.0(bioc 3.20)

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

geneexpression principalcomponent statisticalmethod clustering software

4.28 score 48 scripts 439 downloads 1 mentions 29 exports 62 dependencies

Last updated 23 days agofrom:b1cb18df87. Checks:OK: 1 NOTE: 6. Indexed: yes.

Target	Result	Date
Doc / Vignettes	OK	Nov 19 2024
R-4.5-win	NOTE	Nov 19 2024
R-4.5-linux	NOTE	Nov 19 2024
R-4.4-win	NOTE	Nov 19 2024
R-4.4-mac	NOTE	Nov 19 2024
R-4.3-win	NOTE	Nov 19 2024
R-4.3-mac	NOTE	Nov 19 2024

Exports:annotate.gs bootMbpca bootMoa box.gs.feature combine decompose.gs.group decompose.gs.ind distMoa getmgsa GIS matpower mbpca moa moaCoef moaScore moGap mogsa pairwise.rv plot plotGS prepGraphite prepMsigDB prepSupMoa print show softK summary sup.moa wsvd

Dependencies:annotate AnnotationDbi askpass Biobase BiocGenerics Biostrings bit bit64 bitops blob cachem caTools cli cluster corpcor cpp11 crayon curl DBI fastmap genefilter generics GenomeInfoDb GenomeInfoDbData glue gplots graph graphite GSEABase gtools httr IRanges jsonlite KEGGREST KernSmooth lattice lifecycle magrittr Matrix MatrixGenerics matrixStats memoise mime openssl pkgconfig plogr png purrr R6 rappdirs rlang RSQLite S4Vectors survival svd sys UCSC.utils vctrs XML xtable XVector zlibbioc

moCluster: Integrative clustering using multiple omics data

Rendered frommoCluster-knitr.Rnwusingknitr::knitron Nov 19 2024.

Last update: 2019-05-07
Started: 2019-05-07

mogsa: gene set analysis on multiple omics data

Rendered frommogsa-knitr.Rnwusingknitr::knitron Nov 19 2024.

Last update: 2019-05-07
Started: 2019-05-07

Citation

Development and contributors

Readme and manuals

Help Manual

Help page	Topics
Multiple omics clustering and gene set analysis	mogsa-package
Summary annotation information of a gene set	annotate.gs
NIPALS algorithm with soft thresholding operator on rows and columns	biSoftK
Bootstrap mbpca to estimate the coherence of different data sets	bootMbpca
An internal function called by 'bootMbpca'.	bootMbpcaK
Significant components in "moa" returned by function "moa".	bootMoa
boxplot of gene set variables across all samples.	box.gs.feature
Combine two objects of class 'mgsa' into one.	combine combine,mgsa,mgsa-method combine-methods
Data-wise or PC-wise decomposition of gene set scores for all observations.	decompose.gs.group
Data-wise or PC-wise decomposition of gene set scores for a single observation.	decompose.gs.ind
deflat function used by 'mbpca'	deflat
Calculate the distance matrix from an object of class 'moa-class'.	distMoa
get values in an object of class "mgsa".	getmgsa
calculate gene influential scores of genes in a gene set.	GIS
compute the power of a matrix	matpower
Extension of PCA to analyze multiple data sets	mbpca
Class '"mgsa"'	mgsa-class
Multiple omics data analysis using MFA or STATIS	moa
Class '"moa"'	moa-class plot,moa,missing-method
Class '"moa.sup"'	moa.sup-class
Extract the loadings/coefficients from an object of class 'moa-class'.	moaCoef
Extract global scores from an object of class 'moa-class'.	moaScore
Gap statistic for clustering latent variables in 'moa-class'.	moGap
multiple omics data integration and gene set analysis	mogsa
SVD based algorithm to calculate block Score and global scores for 'mbpca'.	msvd
supp data for Microarray gene expression profiles of the NCI 60 cell lines from 4 different platforms	NCI60_4array_supdata
Microarray gene expression profiles of the NCI 60 cell lines from 4 different platforms	NCI60_4arrays
NIPALS algorithm with soft thresholding operator	nipalsSoftK
pairwise RV coefficients.	pairwise.rv
Methods for function 'plot'	plot-methods
Plot the gene set space	plotGS
Prepare pathway gene sets from graphite package	prepGraphite
Conver gmt format file to a list	prepMsigDB
Prepare sumpplementary tables for projection by sup.moa or mogsa.	prepSupMoa
Methods for function 'print'	print print,mgsa-method print,moa-method print,moa.sup-method print-methods
preprocessing of input data in 'mbpca'.	processOpt
Methods for function 'show'	show show,mgsa-method show,moa-method show,moa.sup-method show-methods
Soft-thresholding operator	softK
Methods for function 'summary'	summary summary,mgsa-method summary,moa-method summary,moa.sup-method summary-methods
Projecting supplementary tables on object of class 'moa-class'.	sup.moa
convert 'mbpca' result to 'moa-class'	toMoa
Weighted singular value decomposition (SVD)	wsvd